Study on Forecasting Public Revenue for Andhra Pradesh State Road Transport Using Regression Techniques

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Forecasting public revenue of transport system indirectly shows the development of system with the growth of economy. Andhra Pradesh state road transport corporation (APSRTC) develops rapidly by this process .Therefore there is a need for developing model to forecast public revenue and identifying the relationship between transportation and economy of the system. The passenger traffic volume collected from the APSRTC for calculating public Revenue is based on the data from 2016 to 2017.Then different regression models are applied on the collected data for analysis purpose. The linear regression outperforms gradient boosting, decision trees and neural networks with a relative error less than 5% for predicting public revenue. The accuracy of models on revenue has been improved which helps for the development of transportation system.

     


  • Keywords


    Public Revenue; Linear Regression; Gradient Boosting.

  • References


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      [2] Draper, N. R., Smith, H., &Pownell, E. (1966). Applied regression analysis (Vol. 3). New York: Wiley.

      [3] Han, Y. H., & Chen, C. (2011). Relationship between freight transportation and economic growth of China. Journal of Beijing Institute ofTechnology, 20, 101-106.

      [4] Gurmu, K.Z.; Fan, W. 2014. Artificial Neural Network Travel Time Prediction Model for Buses using only GPS Data, Journal of Public Transportation, 17(2): 45-65. https://doi.org/10.5038/2375-0901.17.2.3.

      [5] https://mubaris.com/2017/09/28/linear-regression-from-scratch.


 

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Article ID: 14099
 
DOI: 10.14419/ijet.v7i3.18.14099




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